Papers
A Powerful Generative Model Using Random Weights for the Deep Image Representation
Kun He, Yan Wang, John Hopcroft
Applying Spectral Normalisation and Efficient Envelope Estimation and Statistical Transformation for the Voice Conversion Challenge 2016
Fernando Villavicencio, Junichi Yamagishi, Jordi Bonada et al.
Appraising UMLS Coverage for Summarizing Medical Evidence
Elaheh ShafieiBavani, Mohammad Ebrahimi, Raymond Wong et al.
Approximate Inference Using DC Programming For Collective Graphical Models
Thien Nguyen, Akshat Kumar, Hoong Chuin Lau et al.
Approximate Log-Hilbert-Schmidt Distances Between Covariance Operators for Image Classification
Ha Quang Minh, Marco San Biagio, Loris Bazzani et al.
Approximate maximum entropy principles via Goemans-Williamson with applications to provable variational methods
Andrej Risteski, Yuanzhi Li
Approximate Newton Methods for Policy Search in Markov Decision Processes
Thomas Furmston, Guy Lever, David Barber
A Practical Scheme and Fast Algorithm to Tune the Lasso With Optimality Guarantees
Michael Chichignoud, Johannes Lederer, Martin J. Wainwright
A Preliminary Ultrasound Study of Nasal and Lateral Coronals in Arrernte
Marija Tabain, Richard Beare
A primal-dual method for conic constrained distributed optimization problems
Necdet Serhat Aybat, Erfan Yazdandoost Hamedani
A priori SNR Estimation Using a Generalized Decision Directed Approach
Aleksej Chinaev, Reinhold Haeb-Umbach
A Probabilistic Collaborative Representation Based Approach for Pattern Classification
Sijia Cai, Lei Zhang, Wangmeng Zuo et al.
A Probabilistic Framework for Color-Based Point Set Registration
Martin Danelljan, Giulia Meneghetti, Fahad Shahbaz Khan et al.
A Probabilistic Framework for Deep Learning
Ankit B Patel, Minh Tan Nguyen, Richard Baraniuk
A Probabilistic Framework for Real-time 3D Segmentation using Spatial, Temporal, and Semantic Cues
David Held, Devin Guillory, Brice Rebsamen et al.
A Probabilistic Model of Social Decision Making based on Reward Maximization
Koosha Khalvati, Seongmin A. Park, Jean-Claude Dreher et al.
A Probabilistic Programming Approach To Probabilistic Data Analysis
Feras Saad, Vikash K Mansinghka
A Progressive Explanation of Inference in ‘Hybrid’ Bayesian Networks for Supporting Clinical Decision Making
Evangelia Kyrimi, William Marsh
A Proposition-Based Abstractive Summariser
Yimai Fang, Haoyue Zhu, Ewa Muszyńska et al.
A Prototype Automatic Simultaneous Interpretation System
Xiaolin Wang, Andrew Finch, Masao Utiyama et al.
A Pseudo-Bayesian Algorithm for Robust PCA
Tae-Hyun Oh, Yasuyuki Matsushita, In Kweon et al.
A Random Matrix Approach to Echo-State Neural Networks
Romain Couillet, Gilles Wainrib, Hafiz Tiomoko Ali et al.
A ranking approach to global optimization
Cedric Malherbe, Emile Contal, Nicolas Vayatis
Architectural Complexity Measures of Recurrent Neural Networks
Saizheng Zhang, Yuhuai Wu, Tong Che et al.